集装箱卡车配置仿真研究

分析集装箱码头中集装箱卡车传统配置方式的基础上,使用Arena仿真软件,建立集装箱卡车配置仿真模型.基于集装箱卡车最短路径调度法,应用于实际生产的仿真模型,可计算集装箱卡车的最优配置.结果表明集装箱运输量恒定,集卡传统配置方式不是最优.通过建立仿真模型,计算所需要集卡量的最优解,为实际生产中集卡的配置提供理论依据,提高码头机械设备的利用率.     

集装箱码头送箱外集卡预约优化研究

通过预约缓解集装箱码头拥堵是提高港口运作效率的有效途径。考虑集卡公司和码头运营商双方的利益以及码头内部作业系统的复杂性,以减小外集卡在预约时间窗内的平均排队长度和集卡公司期望到达的预约时间窗与被调配到的预约时间窗间的差异为目标,运用排队论相关知识和逐点固定流体近似方法（PSFFA）,建立了多目标规划模型,以确定一个使集卡公司和码头运营商双赢的集卡调度计划。引入实例数据,利用CPLEX求解模型,并将结果与蒙特卡罗仿真结果作比较,以验证模型的有效性,并在此基础上调节参数优化预约模式。算例结果表明,集卡预约多目标规划模型能有效描述集卡在闸口和堆场的排队情况,最小化外集卡在码头排队长度和集卡公司期望到达的预约时间窗与被调配到的预约时间窗之间的差异。     

速度不确定下作业时间最短的集卡调度优化

在集装箱码头装卸作业中,提高集卡调度对作业效率有非常大的影响。而集装箱卡车重车和空车行驶速度的不确定性,增加了集卡调度的难度。为此提出建立不确定环境下作业时间最短的集卡调度优化模型。在完成固定装卸任务的前提下,通过对集卡的合理调度,达到不确定情况下集卡总作业时间最短。针对不确定模型的特点,采用粒子群算法快速求解,同时保证了解的有效性。算例表明上述模型和算法合理解决了不确定环境下集卡调度优化问题,得到较好的计算结果,并且降低了运算复杂度,提高了调度效率。     

不确定环境下的岸桥集卡协调调度耦合模型建立与求解

集装箱码头系统是一个由多个子系统组成的复杂的生产系统,系统内资源的调度也是非线性的复杂问题,同时涉及多种多样的不确定性因素。从不确定性的角度出发,主要考虑码头装卸设备运行参数的概率分布,研究岸桥和集卡之间的协调调度问题。采用多学科变量耦合优化设计的方法,同时考虑了集装箱任务的时间窗约束,分别建立集卡分派子模型和集卡配置子模型。并将完工时刻和集卡数量作为公用设计变量连接两个子模型,建立了协调调度耦合模型。选取上海港某码头的数据编写算例,在Visual Studio 2012环境下调用Gurobi4.0求解该耦合模型,反复迭代计算后得出最优的集卡分派方案相对于最初的调度方案,总延误时间成本下降了90.69%,集卡数量下降了30.76%,验证了本模型的有效性和实用性。     

不确定环境下码头堆场设备集成调度优化

集装箱码头堆场设备调度优化中,对确定条件下的内集卡和场桥的联合调度研究较多,且没有考虑外集卡的随机到达情况。考虑内集卡和场桥作业过程中的不确定性因素,包括：内集卡行驶速度,场桥行走速度和作业时间,并考虑外集卡随机到达堆场对于内集卡调度作业的影响,构建了不确定因素条件下的堆场设备集成调度优化模型,其优化目标是在考虑外集卡随机到达的情况下,最优化堆场设备的作业时间。设计了求解模型的粒子群算法,并比较了一般确定性模型和考虑不确定因素优化模型的结果。算例结果表明,所建立的模型和算法能有效真实地反映不确定因素对集装箱码头堆场设备作业的影响。     

全岸线集装箱装卸桥调度模型研究

集装箱装卸桥是集装箱物流多式联运的关键设备,处于整个集装箱物流的重要节点。集装箱装卸桥的调度计划直接影响集装箱码头的运作效率。通过对集装箱码头装卸桥生产过程的研究,建立全岸线集装箱装卸桥调度与分配的混合整数动态规划模型,并采用基于段编码技术的遗传算法,进行模型优化求解;优化后的集装箱装卸桥调度方案的生产效率和生产作业均衡有明显改善。     

面向哈佛体系结构的集装箱码头场桥作业调度

集装箱码头堆场作业调度问题一直是国内外相关研究的热点和难点,但由于码头作业的动态性、开放性、强耦合性和复杂性,堆场主要装卸设备场桥的调度配置问题一直未能有较好的解决方案。故提出面向哈佛体系结构的基于Agent建模和仿真模式,并将计算机操作系统中的磁盘臂调度算法和基于仿真的优化思想引入到上述模型中。通过构建相应的多Agent系统仿真得出敏捷高效鲁棒的场桥调度和配置解决方案,从而帮助集装箱码头提高服务水平和竞争力。     

集装箱码头装卸作业的调度控制模型及算法设计

对集装箱码头上装卸作业的调度控制直接影响码头的整体运营效率．本文研究了集装箱码头装卸作业的调度控制问题,提出了一个基于柔性化flow shop的集成化控制模型．该问题具有非线性规划(NP：non- polynomial)难度,因此本文开发设计了两类基于优先级规则的启发式调度算法．利用该模型来对码头中多种装卸设备进行总体调度可以提高设备之间的协调性,提高码头效率,降低成本．实验研究证明算法能有效地解决该问题．     

堆场龙门吊调度问题研究

在集装箱码头作业中,龙门吊是非常重要的码头资源,如何更合理地调度龙门吊对减少船舶在港时间,提高码头效率有重要意义。在综合考虑龙门吊在时间和空间上的不可跨越性以及其他约束条件的基础上,建立了龙门吊调度问题的混合整数规划模型,目标是使得集卡的等待时间最短。由于问题计算的复杂性,引进遗传算法来求解模型;算例验证了算法的有效性,与已有的模型进行比较,证明了该模型的优越性。     

MAS在集装箱港口决策支持系统中应用研究

针对集装箱港口物流运作系统的动态性、随机性、分治性和复杂性的特点,建立了以多Agent技术为核心的集装箱港口生产调度系统,以促进集装箱码头各个子系统之间的相互协调,提高集装箱码头设备利用率和码头年吞吐量。系统基于J2EE平台,采用B/S多层架构技术和MVC开发模式。通过在某港口的试运行,表明该系统具有良好的可管理性、可扩展性和可维护性,为集装箱港口物流运作管理提供了良好的技术支持。     

考虑能耗节约的集装箱码头双小车岸桥与AGV联合配置及调度优化

合理调度集装箱码头的装卸设备以减少生产过程中的能耗, 对实现其低碳绿色化发展具有重要意义. 针对集装箱码头向自动化发展过程中的双小车岸桥与AGV (Automated guided vehicle)联合配置及调度问题, 考虑AGV续航时间、双小车岸桥中转平台容量和堆场缓冲支架容量约束, 以岸桥的能耗最小为第一阶段模型的优化目标, 以AGV运输过程的能耗最小为第二阶段目标建立两阶段优化模型; 设计枚举法求解第一阶段模型, 改进遗传算法求解第二阶段优化模型. 以洋山四期自动化集装箱码头为例进行实验分析, 针对不同船舶在港总装卸时间和AGV配置原则进行实验, 验证了模型和算法的有效性, 结果表明以最小化能耗为目标的双小车岸桥与AGV联合调度可在岸桥主小车不延误的前提下, 显著减少AGV的配置数量.     

Layout analysis affecting strategic decisions in artificial container terminals

As a result of a major growth in world trade, importance of the container terminals, which are the exit gates of international maritime trade, has been emphasized and the competition between these terminals has increased. In recent years, increasing competition in shallow seas, which have low berth depth and intensive trade, has caused terminal managers to investigate how the strategic decisions affect the future development of terminal operations. Due to their low berth depth, container terminals in the feeder ports of shallow seas are built artificially near coastlines. The most common layouts found in these terminals are Π, L, π, or Ψ. In this paper, simulation models were developed for the container terminals to examine the effect of transporter dispatching rules and resource allocation strategies in terms of total annual handling amount. According to the results, terminal performance is significantly affected by terminal layout design under different transporter dispatching rules and allocation strategies.     

Integrating simulation and optimization to schedule loading operations in container terminals

In this paper, a simulation optimization method for scheduling loading operations in container terminals is developed. The method integrates the intelligent decision mechanism of optimization algorithm and evaluation function of simulation model, its procedures are: initializing container sequence according to certain dispatching rule, then improving the sequence through genetic algorithm, using simulation model to evaluate objective function of a given scheduling scheme. Meanwhile, a surrogate model based on neural network is designed to predict objective function and filter out potentially bad solutions, thus to decrease the times of running simulation model. Numerical tests show that simulation optimization method can solve the scheduling problem of container terminals efficiently. And the surrogate model can improve the computation efficiency of simulation optimization.     

Dynamic rolling strategy for multi-vessel quay crane scheduling

This paper focuses on the container loading and unloading problem with dynamic ship arrival times. Using a determined berth plan, in combination with the reality of a container terminal production scheduling environment, this paper proposes a scheduling method for quay cranes that can be used for multiple vessels in a container terminal, based on a dynamic rolling-horizon strategy. The goal of this method is to minimize the operation time of all ships at port and obtain operation equilibrium of quay cranes by establishing a mathematical model and using a genetic algorithm to solve the model. Numerical simulations are applied to calculate the optimal loading and unloading order and the completion time of container tasks on a ship. By comparing this result with the traditional method of quay crane loading and unloading, the paper verifies that the quay crane scheduling method for multiple vessels based on a dynamic rolling-horizon strategy can provide a positive contribution to improve the efficiency of container terminal quay crane loading and unloading and reduce resource wastage.     

考虑时间窗的集装箱港口场桥全局调度优化

合理高效的场桥调度计划有助于减少场桥与集卡相互等待的时间从而提高港口的运营效率,考虑到在实际操作中会出现多箱区多场桥同时工作、互相冲突等情况,建立了以场桥移动成本和延误成本最小化为目标的数学模型,利用计划时间段和时间窗的概念对场桥作业进行约束,通过遗传算法编码进行求解,并将计算结果与实际操作及其他算法的优化结果相对比,进而验证该模型和算法的有效性和稳定性。     

铁路集装箱转运作业问题的决策支持模型研究

集装箱转运问题是铁路集装箱物流中心站提高服务效率的关键问题之一,转运过程中涉及到的相关资源配置则是其要解决的核心内容。针对集装箱转运作业流程的特点,利用系统分析方法将转运系统分成门式起重机、内部集装箱运输卡车和正面吊运机/辅助箱场三个子系统,分别对各子系统进行操作时间分析,进而得到整体系统的作业时间模型,由此开发集装箱转运问题的规划调度决策支持系统,为决策者提供决策依据。通过模拟运行结果,得到了集装箱转运过程中所需的所有设备资源的最优组合数量,将模型模拟结果与相应的实际数据进行对比,证明了该模型的可行性。     

An architectural design of control software for automated container terminals

Automation of handling equipment is a current trend in port container terminal. Because a large number of equipment of different types are involved in the handling operation, the structure of control software is highly complicated. This paper introduces an architectural design of control software and a simulation-based test-bed for testing various control rules of the control software. The suggested control system consists of a ship operation manager (SOM) and system controllers for automated guided vehicles (AGVs) and automated yard cranes (AYCs). A SOM is in charge of dispatching tasks to equipment for preplanned load/unload operations. System controllers assign equipment to the SOM and maintain the information about the location and the status of equipment. To test the control system and the operation methods of the suggested container terminal, an object-oriented simulation system was developed using Java. Using the simulation system, several operation-related issues were tested, including the postponement of dispatching decisions and the sequence rearrangement of AGVs entering transfer areas under quay cranes (QCs).